Abstract:
The response of crop productivity and our global food systems to climate change is complex and associated with large uncertainties. Process-based crop modeling allows studying agro-ecoregion under fundamentally different environmental and management conditions and there provides a valuable tool for impact assessment and adaptation planning. Here I present results from various projects around the Agricultural Model Intercomparison and Improvement Project (AgMIP), highlighting the main knowns and unknowns.
Bio:
In my role as an Associate Research Scientist at Columbia University and NASA Goddard Institute for Space Studies, I lead various international projects and initiatives that help improve our understanding of climate, management, and breeding responses in global agriculture. For example, I lead the Global Gridded Crop Model Intercomparison Project (GGCMI) and coordinate the agriculture sector in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Leveraging ensembles of leading process-based crop models, my research ranges across topics including climate change impacts in global agriculture, seasonal to decadal yield prediction, breeding requirements for climate resilient food systems, indirect effects of nuclear conflict on global food security, and many more.